Deep Learning-assisted Tracking of Bubble Dynamics for Elucidating Oxygen Evolution Reaction on Nickel Electrodes

The oxygen evolution reaction (OER) involves multiple proton-coupled electron transfer steps and complex reaction intermediates. The influence of interfacial gas evolution on its kinetic responses remains difficult to understand. In this study, nickel electrodes were employed as a model system to elucidate the relationship between O2 bubble dynamics and electrochemical behavior under electrochemical potential control. Video observation coupled with a deep learning analysis pipeline enabled precise recognition and temporal tracking of O2 bubbles during OER. Quantitative analysis of bubble growth enabled the extraction of current densities based on bubble growth. These findings highlight the critical role of interfacial gas dynamics in governing the kinetics of multi-electron transfer reactions and provide a new framework for mechanistic analysis of OER with respect to the conventional electrochemical measurements.